Hospitals are beginning to monitor CT radiation dose in response to issued health guidelines. When undergoing medical radiation exposure, including that of computed tomography (CT), the guiding principle is that of As Low As Reasonably Achievable (ALARA). Thus, imagers desire to use the minimum radiation dose necessary to achieve diagnostic image quality. Radiation doses that are too low produce images of inadequate quality. Radiation doses that are too high place the patient at risk without added diagnostic quality. Therefore, the problem of ALARA in CT may be viewed as an image quality optimization problem in addition to a radiation dose optimization problem. Specifically, imagers' ability to optimize dose depends on their ability to accurately predict image quality prior to the CT examination and prospectively use radiation dose parameters that will result in image quality that is just above the diagnostic threshold.
All else being equal, higher radiation dose in a CT scanner results in a clearer image. Two major factors under the direct control of the operator contribute to the radiation dose: the energy level of the beam, measured as the tube voltage (kV), and the fluence of photons, measured as a function of the tube current and time (mAs). Radiation dose delivered to the patient is proportional to the fluence and approximately proportional to the square of the tube current. Lowering the dose reduces the number of photons arriving at the detector and results in a grainier, or noisier, image. Higher dose levels are required to maintain image quality in larger patients and lower dose levels are required in smaller patients. The goal for the operator is to use the lowest radiation dose possible to generate images of diagnostic quality. To date, image quality measurements for clinical examinations are typically not available to radiologists.
The limiting image quality characteristic for low-contrast applications such as CT of the abdomen/pelvis tends to be that of low contrast detectability (LCD), which incorporates both spatial and contrast resolution estimates. The method of measuring image quality for the present disclosure is that of image noise, which can be used as a proxy for LCD as it provides a single image quality measure. CT parameters must be set prior to the examination; therefore, if parameters are to be based on a minimum image quality, the user must know a priori what parameters should be used that will result in the lowest radiation dose possible to generate images of diagnostic quality.
Several radiation reduction techniques, including dose modulation, are incorporated into most modern CT scanners. However, radiation dose remains under the control of the operator, who retains the ability to set scan parameters such as kV, mA, and acceptable “noise factor” parameters for dose modulated examinations. Yet radiologists are still currently limited in many respects, including the following:                a) Image quality is difficult to quantify, even by visual inspection; thus, standard image quality metrics have not been well established.        b) Image quality depends on both scan parameters and patient size; a quantitative model of how these factors interact to impact image quality has not been well established.        c) Even if it could be measured, without a predictive model, image quality can only be assessed after the scan has been completed, limiting its usefulness.        d) Minimum image quality thresholds have not been established.        
Furthermore, CT utilization has substantially increased in recent years. Many scanners perform dozens of examinations per day, operated by CT technologists, supervised by radiologists, with the aid of physicists, none of whom are currently reimbursed for optimizing image quality or radiation dose. It would be unreasonable to expect that these individuals would dedicate a large amount of their time to ensure image quality/dose optimization. Thus, even if a method of quantifying image quality is developed, unless it is integrated into the current workflow with minimal disruption and is easy to use, it is unlikely to experience widespread adoption.
Many of the current challenges surrounding CT dose optimization are related to the problem of image quality and dose verification. Without an automated system, radiologists who believe or claim that they optimize dose can only verify this at great expense, if at all, due to the difficulty in acquiring, analyzing, aggregating, and reporting data from individual scans.
Thus, while quantitative image quality assessment is an important element, the system must also be practical. Specifically, the system should satisfy several principles:                1. Prediction: The system should predict image quality based on scan parameters and patient size.        2. Optimization: The system should recommend scan parameters that are expected to produce images of desired quality at the lowest possible dose (ALARA).        3. Assessment: The system should assess how well an individual scan achieves the goal of ALARA relative to other scans.        4. Monitoring: The system should enable a manager to ensure that ALARA is consistently achieved on all studies on all scanners in an organization.        5. Verification/reporting: The system should enable an enterprise to report its performance in a quantifiable way.        6. Automation/integration: To the extent possible, the system should function automatically, requiring minimal manual data input.        7. Transparency: At the same time, the system should be as transparent as possible, informing operators and managers of both individual and aggregated study performance.        8. Controllable: While the system should function automatically, it should also allow overriding operator control at any time.        9. Ease of use: The system should be intuitive and as simple to use as possible.        